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Anonymizing Health Data


Anonymizing Health Data
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Anonymizing Health Data


Anonymizing Health Data
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Author : Khaled El Emam
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2013-12-11

Anonymizing Health Data written by Khaled El Emam and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-12-11 with Computers categories.


Updated as of August 2014, this practical book will demonstrate proven methods for anonymizing health data to help your organization share meaningful datasets, without exposing patient identity. Leading experts Khaled El Emam and Luk Arbuckle walk you through a risk-based methodology, using case studies from their efforts to de-identify hundreds of datasets. Clinical data is valuable for research and other types of analytics, but making it anonymous without compromising data quality is tricky. This book demonstrates techniques for handling different data types, based on the authors’ experiences with a maternal-child registry, inpatient discharge abstracts, health insurance claims, electronic medical record databases, and the World Trade Center disaster registry, among others. Understand different methods for working with cross-sectional and longitudinal datasets Assess the risk of adversaries who attempt to re-identify patients in anonymized datasets Reduce the size and complexity of massive datasets without losing key information or jeopardizing privacy Use methods to anonymize unstructured free-form text data Minimize the risks inherent in geospatial data, without omitting critical location-based health information Look at ways to anonymize coding information in health data Learn the challenge of anonymously linking related datasets



Sharing Clinical Trial Data


Sharing Clinical Trial Data
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Author : Institute of Medicine
language : en
Publisher: National Academies Press
Release Date : 2015-04-20

Sharing Clinical Trial Data written by Institute of Medicine and has been published by National Academies Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-04-20 with Medical categories.


Data sharing can accelerate new discoveries by avoiding duplicative trials, stimulating new ideas for research, and enabling the maximal scientific knowledge and benefits to be gained from the efforts of clinical trial participants and investigators. At the same time, sharing clinical trial data presents risks, burdens, and challenges. These include the need to protect the privacy and honor the consent of clinical trial participants; safeguard the legitimate economic interests of sponsors; and guard against invalid secondary analyses, which could undermine trust in clinical trials or otherwise harm public health. Sharing Clinical Trial Data presents activities and strategies for the responsible sharing of clinical trial data. With the goal of increasing scientific knowledge to lead to better therapies for patients, this book identifies guiding principles and makes recommendations to maximize the benefits and minimize risks. This report offers guidance on the types of clinical trial data available at different points in the process, the points in the process at which each type of data should be shared, methods for sharing data, what groups should have access to data, and future knowledge and infrastructure needs. Responsible sharing of clinical trial data will allow other investigators to replicate published findings and carry out additional analyses, strengthen the evidence base for regulatory and clinical decisions, and increase the scientific knowledge gained from investments by the funders of clinical trials. The recommendations of Sharing Clinical Trial Data will be useful both now and well into the future as improved sharing of data leads to a stronger evidence base for treatment. This book will be of interest to stakeholders across the spectrum of research-from funders, to researchers, to journals, to physicians, and ultimately, to patients.



Privacy Preserving Data Publishing


Privacy Preserving Data Publishing
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Author : Bee-Chung Chen
language : en
Publisher: Now Publishers Inc
Release Date : 2009

Privacy Preserving Data Publishing written by Bee-Chung Chen and has been published by Now Publishers Inc this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with Business & Economics categories.


This book is dedicated to those who have something to hide. It is a book about "privacy preserving data publishing" -- the art of publishing sensitive personal data, collected from a group of individuals, in a form that does not violate their privacy. This problem has numerous and diverse areas of application, including releasing Census data, search logs, medical records, and interactions on a social network. The purpose of this book is to provide a detailed overview of the current state of the art as well as open challenges, focusing particular attention on four key themes: RIGOROUS PRIVACY POLICIES Repeated and highly-publicized attacks on published data have demonstrated that simplistic approaches to data publishing do not work. Significant recent advances have exposed the shortcomings of naive (and not-so-naive) techniques. They have also led to the development of mathematically rigorous definitions of privacy that publishing techniques must satisfy; METRICS FOR DATA UTILITY While it is necessary to enforce stringent privacy policies, it is equally important to ensure that the published version of the data is useful for its intended purpose. The authors provide an overview of diverse approaches to measuring data utility; ENFORCEMENT MECHANISMS This book describes in detail various key data publishing mechanisms that guarantee privacy and utility; EMERGING APPLICATIONS The problem of privacy-preserving data publishing arises in diverse application domains with unique privacy and utility requirements. The authors elaborate on the merits and limitations of existing solutions, based on which we expect to see many advances in years to come.



Guide To The De Identification Of Personal Health Information


Guide To The De Identification Of Personal Health Information
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Author : Khaled El Emam
language : en
Publisher: CRC Press
Release Date : 2013-05-06

Guide To The De Identification Of Personal Health Information written by Khaled El Emam and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-05-06 with Business & Economics categories.


Offering compelling practical and legal reasons why de-identification should be one of the main approaches to protecting patients' privacy, the Guide to the De-Identification of Personal Health Information outlines a proven, risk-based methodology for the de-identification of sensitive health information. It situates and contextualizes this risk-ba



Privacy Preserving Data Mining


Privacy Preserving Data Mining
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Author : Charu C. Aggarwal
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-06-10

Privacy Preserving Data Mining written by Charu C. Aggarwal and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-06-10 with Computers categories.


Advances in hardware technology have increased the capability to store and record personal data about consumers and individuals, causing concerns that personal data may be used for a variety of intrusive or malicious purposes. Privacy-Preserving Data Mining: Models and Algorithms proposes a number of techniques to perform the data mining tasks in a privacy-preserving way. These techniques generally fall into the following categories: data modification techniques, cryptographic methods and protocols for data sharing, statistical techniques for disclosure and inference control, query auditing methods, randomization and perturbation-based techniques. This edited volume contains surveys by distinguished researchers in the privacy field. Each survey includes the key research content as well as future research directions. Privacy-Preserving Data Mining: Models and Algorithms is designed for researchers, professors, and advanced-level students in computer science, and is also suitable for industry practitioners.



Database Technology For Life Sciences And Medicine


Database Technology For Life Sciences And Medicine
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Author : Claudia Plant
language : en
Publisher: World Scientific
Release Date : 2010

Database Technology For Life Sciences And Medicine written by Claudia Plant and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Computers categories.


This book presents innovative approaches from database researchers supporting the challenging process of knowledge discovery in biomedicine. Ranging from how to effectively store and organize biomedical data via data quality and case studies to sophisticated data mining methods, this book provides the state-of-the-art of database technology for life sciences and medicine. A valuable source of information for experts in life sciences who want to be updated about the possibilities of database technology in their field, this volume will also be inspiring for students and researchers in informatics who are keen to contribute to this emerging field of interdisciplinary research.



Analyzing Qualitative Data


Analyzing Qualitative Data
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Author : Graham R Gibbs
language : en
Publisher: SAGE
Release Date : 2018-09-03

Analyzing Qualitative Data written by Graham R Gibbs and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-03 with Social Science categories.


This book tackles the challenges of how to make sense of qualitative data. It offers students and researchers a hands-on guide to the practicalities of coding, comparing data, and using computer-assisted qualitative data analysis. Lastly, Gibbs shows you how to bring it all together, so you can see the steps of qualitative analysis, understand the central place of coding, ensure analytic quality and write effectively to present your results.



Advances In Digital Health And Medical Bioengineering


Advances In Digital Health And Medical Bioengineering
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Author : Hariton-Nicolae Costin
language : en
Publisher: Springer Nature
Release Date : 2024-08-31

Advances In Digital Health And Medical Bioengineering written by Hariton-Nicolae Costin and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-31 with Technology & Engineering categories.


This book gathers the proceedings of the 11th International Conference on E-Health and Bioengineering, EHB2023, held in hybrid form on November 9–10, 2023, in/from Bucharest, Romania. This second volume of a 3-volume set reports on methods for and results from health technology assessment processes, on advances in biosignal processing, medical imaging, informatics and big data in medicine, and current knowledge concerning the design and evaluation of medical devices. It addresses a broad audience of researchers and professionals working at the interface between medicine, informatics, bioengineering, and electrical and mechanical engineering.



Introduction To Privacy Preserving Data Publishing


Introduction To Privacy Preserving Data Publishing
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Author : Benjamin C.M. Fung
language : en
Publisher: Chapman and Hall/CRC
Release Date : 2010-08-02

Introduction To Privacy Preserving Data Publishing written by Benjamin C.M. Fung and has been published by Chapman and Hall/CRC this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-08-02 with Computers categories.


Gaining access to high-quality data is a vital necessity in knowledge-based decision making. But data in its raw form often contains sensitive information about individuals. Providing solutions to this problem, the methods and tools of privacy-preserving data publishing enable the publication of useful information while protecting data privacy. Introduction to Privacy-Preserving Data Publishing: Concepts and Techniques presents state-of-the-art information sharing and data integration methods that take into account privacy and data mining requirements. The first part of the book discusses the fundamentals of the field. In the second part, the authors present anonymization methods for preserving information utility for specific data mining tasks. The third part examines the privacy issues, privacy models, and anonymization methods for realistic and challenging data publishing scenarios. While the first three parts focus on anonymizing relational data, the last part studies the privacy threats, privacy models, and anonymization methods for complex data, including transaction, trajectory, social network, and textual data. This book not only explores privacy and information utility issues but also efficiency and scalability challenges. In many chapters, the authors highlight efficient and scalable methods and provide an analytical discussion to compare the strengths and weaknesses of different solutions.



Mastering Secure Data Anonymization And Pseudonymization A Comprehensive Framework For Privacy And Compliance In The Digital Age


Mastering Secure Data Anonymization And Pseudonymization A Comprehensive Framework For Privacy And Compliance In The Digital Age
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Author : Sumanth Tatineni
language : en
Publisher: Libertatem Media Private Limited
Release Date : 2024-03-29

Mastering Secure Data Anonymization And Pseudonymization A Comprehensive Framework For Privacy And Compliance In The Digital Age written by Sumanth Tatineni and has been published by Libertatem Media Private Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-29 with Computers categories.


This book delves into the innovative framework for data anonymization and pseudonymization designed to safeguard Personally Identifiable Information (PII) in an era of heightened data privacy concerns and regulatory requirements. With the rapid growth of digital data and stringent regulations like GDPR and HIPAA, organizations face an urgent need to protect sensitive information without sacrificing its utility. Drawing from a patent-pending framework, this book offers a deep exploration into the methodologies, technologies, and applications of secure data handling practices. It provides readers with a step-by-step understanding of the framework's components, including machine learning-based PII detection, advanced anonymization techniques, and controlled re-identification processes. Through real-world examples, practical applications, and insights into regulatory compliance, this book equips professionals, researchers, and policymakers with the knowledge and tools needed to navigate the complexities of data privacy. Readers will gain a comprehensive understanding of how to implement secure data anonymization and pseudonymization, ensuring both privacy and operational efficiency, and learn how to integrate these practices seamlessly into existing data management workflows.